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Null hypothesis significance testing: a short tutorial
Although thoroughly criticized, null hypothesis significance testing (NHST) remains the statistical method of choice used to provide evidence for an effect, in biological, biomedical and social sciences. In this short tutorial, I first summarize the concepts behind the method, distinguishing test of...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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F1000Research
2016
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635437/ https://www.ncbi.nlm.nih.gov/pubmed/29067159 http://dx.doi.org/10.12688/f1000research.6963.3 |
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author | Pernet, Cyril |
author_facet | Pernet, Cyril |
author_sort | Pernet, Cyril |
collection | PubMed |
description | Although thoroughly criticized, null hypothesis significance testing (NHST) remains the statistical method of choice used to provide evidence for an effect, in biological, biomedical and social sciences. In this short tutorial, I first summarize the concepts behind the method, distinguishing test of significance (Fisher) and test of acceptance (Newman-Pearson) and point to common interpretation errors regarding the p-value. I then present the related concepts of confidence intervals and again point to common interpretation errors. Finally, I discuss what should be reported in which context. The goal is to clarify concepts to avoid interpretation errors and propose reporting practices. |
format | Online Article Text |
id | pubmed-5635437 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | F1000Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-56354372017-10-23 Null hypothesis significance testing: a short tutorial Pernet, Cyril F1000Res Opinion Article Although thoroughly criticized, null hypothesis significance testing (NHST) remains the statistical method of choice used to provide evidence for an effect, in biological, biomedical and social sciences. In this short tutorial, I first summarize the concepts behind the method, distinguishing test of significance (Fisher) and test of acceptance (Newman-Pearson) and point to common interpretation errors regarding the p-value. I then present the related concepts of confidence intervals and again point to common interpretation errors. Finally, I discuss what should be reported in which context. The goal is to clarify concepts to avoid interpretation errors and propose reporting practices. F1000Research 2016-10-10 /pmc/articles/PMC5635437/ /pubmed/29067159 http://dx.doi.org/10.12688/f1000research.6963.3 Text en Copyright: © 2016 Pernet C http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Opinion Article Pernet, Cyril Null hypothesis significance testing: a short tutorial |
title | Null hypothesis significance testing: a short tutorial |
title_full | Null hypothesis significance testing: a short tutorial |
title_fullStr | Null hypothesis significance testing: a short tutorial |
title_full_unstemmed | Null hypothesis significance testing: a short tutorial |
title_short | Null hypothesis significance testing: a short tutorial |
title_sort | null hypothesis significance testing: a short tutorial |
topic | Opinion Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635437/ https://www.ncbi.nlm.nih.gov/pubmed/29067159 http://dx.doi.org/10.12688/f1000research.6963.3 |
work_keys_str_mv | AT pernetcyril nullhypothesissignificancetestingashorttutorial |